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Explainable AI
Worried About an Adversarial Attack on your AI?
Worried About an Adversarial Attack on your AI?
Dr. Javad Shafiee explains how to fine-tune your way to a strong defense!
DarwinAI
Feb 26, 2021
COVID-NET CT-2: An Evolutionary Leap
COVID-NET CT-2: An Evolutionary Leap
An update from DarwinAI’s CEO, Sheldon Fernandez about the COVID-NET project.
Sheldon Fernandez
Jan 26, 2021
Using Explainable AI to Improve Personalized Drug Response Prediction
Using Explainable AI to Improve Personalized Drug Response Prediction
By: Dr. Alexander Wong
DarwinAI
Jan 25, 2021
How Much Can We Really Trust You? — A paper on deep neural networks
How Much Can We Really Trust You? — A paper on deep neural networks
Towards Simple, Interpretable Trust Quantification Metrics for Deep Neural Networks
DarwinAI
Jan 22, 2021
TinySpeech: Attention Condensers for Deep Speech Recognition Neural Networks on Edge Devices
TinySpeech: Attention Condensers for Deep Speech Recognition Neural Networks on Edge Devices
TL;DR: Our new attention condenser architecture enables high-performing deep neural networks for robust deep learning on the edge. It…
DarwinAI
Jan 22, 2021
Beyond Explainability: Quantifying the Trustworthiness of a Neural Network
Beyond Explainability: Quantifying the Trustworthiness of a Neural Network
Explainability tells us how AI works, but says nothing about when it can be trusted. This limitation must be confronted.
Sheldon Fernandez
Nov 10, 2020
COVID-Net-S: A neural network to detect COVID Severity
COVID-Net-S: A neural network to detect COVID Severity
Dear Colleagues,
Sheldon Fernandez
Sep 21, 2020
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